Search Results - "Tat-Seng Chua"

Attributed Social Network Embedding by Liao, Lizi, He, Xiangnan, Zhang, Hanwang, Chua, Tat-Seng

“…Embedding network data into a low-dimensional vector space has shown promising performance for many real-world applications, such as node classification and…”
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Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure by Feng, Fuli, He, Xiangnan, Tang, Jie, Chua, Tat-Seng

“…Recent efforts show that neural networks are vulnerable to small but intentional perturbations on input features in visual classification tasks. Due to the…”
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NAIS: Neural Attentive Item Similarity Model for Recommendation by He, Xiangnan, He, Zhankui, Song, Jingkuan, Liu, Zhenguang, Jiang, Yu-Gang, Chua, Tat-Seng

“…Item-to-item collaborative filtering ( aka. item-based CF) has been long used for building recommender systems in industrial settings, owing to its…”
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Video Moment Retrieval With Cross-Modal Neural Architecture Search by Yang, Xun, Wang, Shanshan, Dong, Jian, Dong, Jianfeng, Wang, Meng, Chua, Tat-Seng

“…The task of video moment retrieval (VMR) is to retrieve the specific video moment from an untrimmed video, according to a textual query. It is a challenging…”
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Adversarial Training Towards Robust Multimedia Recommender System by Tang, Jinhui, Du, Xiaoyu, He, Xiangnan, Yuan, Fajie, Tian, Qi, Chua, Tat-Seng

“…With the prevalence of multimedia content on the Web, developing recommender solutions that can effectively leverage the rich signal in multimedia data is in…”
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Meta-Transfer Learning Through Hard Tasks by Sun, Qianru, Liu, Yaoyao, Chen, Zhaozheng, Chua, Tat-Seng, Schiele, Bernt

“…Meta-learning has been proposed as a framework to address the challenging few-shot learning setting. The key idea is to leverage a large number of similar…”
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Real-Time Multimedia Social Event Detection in Microblog by Zhao, Sicheng, Gao, Yue, Ding, Guiguang, Chua, Tat-Seng

“…Detecting events from massive social media data in social networks can facilitate browsing, search, and monitoring of real-time events by corporations,…”
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Affective Image Content Analysis: Two Decades Review and New Perspectives by Zhao, Sicheng, Yao, Xingxu, Yang, Jufeng, Jia, Guoli, Ding, Guiguang, Chua, Tat-Seng, Schuller, Bjorn W., Keutzer, Kurt

“…Images can convey rich semantics and induce various emotions in viewers. Recently, with the rapid advancement of emotional intelligence and the explosive…”
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Fast Matrix Factorization With Nonuniform Weights on Missing Data by He, Xiangnan, Tang, Jinhui, Du, Xiaoyu, Hong, Richang, Ren, Tongwei, Chua, Tat-Seng

“…Matrix factorization (MF) has been widely used to discover the low-rank structure and to predict the missing entries of data matrix. In many real-world…”
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Predicting Personalized Image Emotion Perceptions in Social Networks by Zhao, Sicheng, Yao, Hongxun, Gao, Yue, Ding, Guiguang, Chua, Tat-Seng

“…Images can convey rich semantics and induce various emotions to viewers. Most existing works on affective image analysis focused on predicting the dominant…”
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Hierarchical Attention Network for Visually-Aware Food Recommendation by Gao, Xiaoyan, Feng, Fuli, He, Xiangnan, Huang, Heyan, Guan, Xinyu, Feng, Chong, Ming, Zhaoyan, Chua, Tat-Seng

“…Food recommender systems play an important role in assisting users to identify the desired food to eat. Deciding what food to eat is a complex and…”
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SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning by Long Chen, Hanwang Zhang, Jun Xiao, Liqiang Nie, Jian Shao, Wei Liu, Tat-Seng Chua

“…Visual attention has been successfully applied in structural prediction tasks such as visual captioning and question answering. Existing visual attention…”
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Visual Translation Embedding Network for Visual Relation Detection by Hanwang Zhang, Kyaw, Zawlin, Shih-Fu Chang, Tat-Seng Chua

“…Visual relations, such as person ride bike and bike next to car, offer a comprehensive scene understanding of an image, and have already shown their great…”
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Reinforced Causal Explainer for Graph Neural Networks by Wang, Xiang, Wu, Yingxin, Zhang, An, Feng, Fuli, He, Xiangnan, Chua, Tat-Seng

“…Explainability is crucial for probing graph neural networks (GNNs), answering questions like "Why the GNN model makes a certain prediction?". Feature…”
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Toward Scalable Systems for Big Data Analytics: A Technology Tutorial by Hu, Han, Wen, Yonggang, Chua, Tat-Seng, Li, Xuelong

“…Recent technological advancements have led to a deluge of data from distinctive domains (e.g., health care and scientific sensors, user-generated data,…”
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Learning to Recommend With Multiple Cascading Behaviors by Gao, Chen, He, Xiangnan, Gan, Dahua, Chen, Xiangning, Feng, Fuli, Li, Yong, Chua, Tat-Seng, Yao, Lina, Song, Yang, Jin, Depeng

“…Most existing recommender systems leverage user behavior data of one type only, such as the purchase behavior in E-commerce that is directly related to the…”
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A Study of Multi-Task and Region-Wise Deep Learning for Food Ingredient Recognition by Chen, Jingjing, Zhu, Bin, Ngo, Chong-Wah, Chua, Tat-Seng, Jiang, Yu-Gang

“…Food recognition has captured numerous research attention for its importance for health-related applications. The existing approaches mostly focus on the…”
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Variational Cross-Graph Reasoning and Adaptive Structured Semantics Learning for Compositional Temporal Grounding by Li, Juncheng, Tang, Siliang, Zhu, Linchao, Zhang, Wenqiao, Yang, Yi, Chua, Tat-Seng, Wu, Fei, Zhuang, Yueting

“…Temporal grounding is the task of locating a specific segment from an untrimmed video according to a query sentence. This task has achieved significant…”
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Hierarchical User Intent Graph Network for Multimedia Recommendation by Wei, Yinwei, Wang, Xiang, He, Xiangnan, Nie, Liqiang, Rui, Yong, Chua, Tat-Seng

“…Understanding user preference on item context is the key to acquire a high-quality multimedia recommendation. Typically, the pre-existing features of items are…”
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Learning to Double-Check Model Prediction From a Causal Perspective by Deng, Xun, Feng, Fuli, Wang, Xiang, He, Xiangnan, Zhang, Hanwang, Chua, Tat-Seng

“…The present machine learning schema typically uses a one-pass model inference (e.g., forward propagation) to make predictions in the testing phase. It is…”
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